The present invention relates to the processing of signals obtained from a medical diagnostic apparatus, such a pulse oximeter, using near infrared spectroscopy, to remove artifact or noise effects from the signal representative of a physiological parameter of interest.
A typical pulse oximeter measures two physiological parameters, percent oxygen saturation of arterial blood hemoglobin (SpO2 or sat) and pulse rate. Oxygen saturation can be estimated using various techniques. In one common technique, the photocurrent generated by the photo-detector is conditioned and processed to determine the ratio of modulation ratios (ratio of ratios) of the red to infrared signals. This modulation ratio has been observed to correlate well to arterial oxygen saturation. The pulse oximeters and sensors are empirically calibrated by measuring the modulation ratio over a range of in vivo measured arterial oxygen saturations (SaO2) on a set of patients, healthy volunteers, or animals. The observed correlation is used in an inverse manner to estimate blood oxygen saturation (SpO2) based on the measured value of modulation ratios of a patient. Most pulse oximeters extract the plethysmographic signal having first determined saturation or pulse rate, both of which are susceptible to interference.
In general, pulse oximetry takes advantage of the fact that in live human tissue, hemoglobin is a strong absorber of light between the wavelengths of 500 and 1100 nm. The pulsation of arterial blood through tissue is readily measurable, using light absorption by hemoglobin in this wavelength range. A graph of the arterial pulsation waveform as a function of time is referred to as an optical plethysmograph. The amplitude of the plethysmographic waveform varies as a function of the wavelength of the light used to measure it, as determined by the absorption properties of the blood pulsing through the arteries. By combining plethysmographic measurements at two different wavelength regions, where oxy- and deoxy-hemoglobin have different absorption coefficients, the oxygen saturation of arterial blood can be estimated. Typical wavelengths employed in commercial pulse oximeters are 660 and 890 nm.
It is known that rapid motion or application of pressure to a tissue site can have the effect of changing the optical properties being measured at or near that site. The amplitude of the optical signal changes associated with such events, known as motion artifacts, can easily be larger than that due to the arterial pulse. In practice, this can lead to inaccurate estimation of the percent oxygen saturation by pulse oximetry. Various techniques for addressing and removing undesired signal effects, including motion artifacts are known. As used herein, noise refers to signal portions that are undesired or are not directly related to changes in optical properties that are related to the arterial pulse, and which may include motion artifact. The optical signal through the tissue can be degraded by both noise and motion artifact. One source of noise is ambient light which reaches the light detector. Another source of noise is electromagnetic coupling from other electronic instruments. Motion of the patient also introduces noise and affects the signal. For example, the contact between the detector and the skin, or the emitter and the skin, can be temporarily disrupted when motion causes either to move away from the skin. In addition, since blood is a fluid, it responds differently than the surrounding tissue to inertial effects, thus resulting in momentary changes in volume at the point near which the oximeter probe is attached.
Motion artifact can degrade a pulse oximetry signal relied upon by a health care provider, without the provider's awareness. This is especially true if the monitoring of the patient is remote, the motion is too small to be observed, or the health care provider is watching the instrument or other parts of the patient, and not the sensor site. There are various known techniques for addressing the effects of noise and/or motion artifacts.
For example, U.S. Pat. No. 4,714,341 discloses a method for combining three wavelengths to detect the presence of motion. The wavelengths are used two at a time to separately compute the oxygen saturation percentage. When the oxygen saturation values computed using different wavelength combinations are in poor agreement, this is assumed to be caused by motion artifact, and the value is discarded. A disadvantage of this approach is that the agreement or lack thereof between the saturation values may or may not be due to motion artifact. In addition, this approach does not identify or remove the effects of motion artifact, but instead discards values that appear suspect.
Another approach involves the filtering of pulse oximetry signals. However, filtering methods require assumptions about the properties of the artifact that do not always hold in practice. In addition, this approach does not measure the motion-induced signal.
U.S. Pat. No. 5,482,036 provides another approach, and describes a signal processing method for artifact reduction that functions when the artifact-related signal is associated with blood that is at a lower oxygen saturation than the arterial blood. Such a method relies on the generation of an artificial noise signal, which is combined with the physiological parameter to reduce the effect of the unknown noise signal. This approach for reducing the effects of artifact, without separately measuring the motion signal, is based on assumptions about the effect of motion on the plethysmographic signal. Assumptions may or may not be true, and many assumptions are invalid.
Each of the known techniques for compensating for motion artifact has its own limitations and drawbacks. It is therefore desirable that a pulse oximetry system be designed which more effectively and accurately reports blood-oxygen levels during periods of motion. While many have attempted to isolate the effects of undesired signal portions, such as motion-induced artifacts, by making potentially invalid assumptions or by rejecting suspect estimates of desired signal values, there still remains a need for a deterministic identification, determination and measurement of artifact signals, to enable an accurate measurement of the desired signal values in the presence of undesired signal portions.